Recent applications to biomolecular science and DNA computing have created a new audience for automata theory and formal languages. This is the only introductory book to cover such applications. It ...begins with a clear and readily understood exposition of the fundamentals that assumes only a background in discrete mathematics. The first five chapters give a gentle but rigorous coverage of basic ideas as well as topics not found in other texts at this level, including codes, retracts and semiretracts. Chapter 6 introduces combinatorics on words and uses it to describe a visually inspired approach to languages. The final chapter explains recently-developed language theory coming from developments in bioscience and DNA computing. With over 350 exercises (for which solutions are available), many examples and illustrations, this text will make an ideal contemporary introduction for students; others, new to the field, will welcome it for self-learning.
Purpose - 2010 marked the 50th anniversary of Douglas McGregor's publication of The Human Side of Enterprise. The purpose of this paper is to revisit McGregor's classic book to establish some of his ...principles that are still being utilized today, as well as some that have been forgotten or discarded.Design methodology approach - This paper utilizes specific quotes to establish McGregor's "lessons". They are placed in historical context, and evaluated, through a selected literature review.Findings - Among the lessons learned is the fact that management can be systematically studied, successful management involves creating a particular type of environment, and employee diversity is a major asset for organizations. Included among the lessons lost are: management requires us to develop cause and effect models, management should focus upon the employees reaching self-actualization, authority is a weak management tool, and management is the source of employee problems.Practical implications - It behooves any scientific field to revisit its founding principles, particularly to review what essential lessons might have been misplaced over time.Originality value - McGregor's general "Theory X Theory Y" are well known, but seldom are the principles he laid out in creating the model explored, nor are they compared to modern management practices.
Olive oil, derived from the olive tree (Olea europaea L.), is used in cooking, cosmetics, and soap production. Due to its high value, some producers adulterate olive oil with cheaper edible oils or ...fraudulently mislabel oils as olive to increase profitability. Adulterated products can cause allergic reactions in sensitive individuals and can lack compounds which contribute to the perceived health benefits of olive oil, and its corresponding premium price.
There is a need for robust methods to rapidly authenticate olive oils. By utilising machine learning models trained on the nuclear magnetic resonance (NMR) spectra of known olive oil and edible oils, samples can be classified as olive and authenticated. While high-field NMRs are commonly used for their superior resolution and sensitivity, they are generally prohibitively expensive to purchase and operate for routine screening purposes. Low-field benchtop NMR presents an affordable alternative.
We compared the predictive performance of partial least squares discrimination analysis (PLS-DA) models trained on low-field 60 MHz benchtop proton (
H) NMR and high-field 400 MHz
H NMR spectra. The data were acquired from a sample set consisting of 49 extra virgin olive oils (EVOOs) and 45 other edible oils.
We demonstrate that PLS-DA models trained on low-field NMR spectra are highly predictive when classifying EVOOs from other oils and perform comparably to those trained on high-field spectra. We demonstrated that variance was primarily driven by regions of the spectra arising from olefinic protons and ester protons from unsaturated fatty acids in models derived from data at both field strengths.
Case studies on nine mid-size Chinese organizations were created to establish whether or not the long-recognized principle that increasing environmental uncertainty must be met with organizations ...adopting organic structural elements still holds true. China offers a unique opportunity for such a test in that no other country has experienced so many changes, so quickly. Four conclusions appear: 1) there is a strong evidence that organic structures are still best for organizations operating in environmental uncertainty; 2) organic structures can be embraced by Chinese organizations; 3) Chinese managers view structural change as an on-going process rather than a one-time event; 4) resistance to structural change is as much a problem in China as it is in the West.
Introduction
Olive oil, derived from the olive tree (Olea europaea L.), is used in cooking, cosmetics, and soap production. Due to its high value, some producers adulterate olive oil with cheaper ...edible oils or fraudulently mislabel oils as olive to increase profitability. Adulterated products can cause allergic reactions in sensitive individuals and can lack compounds which contribute to the perceived health benefits of olive oil, and its corresponding premium price.
Objective
There is a need for robust methods to rapidly authenticate olive oils. By utilising machine learning models trained on the nuclear magnetic resonance (NMR) spectra of known olive oil and edible oils, samples can be classified as olive and authenticated. While high‐field NMRs are commonly used for their superior resolution and sensitivity, they are generally prohibitively expensive to purchase and operate for routine screening purposes. Low‐field benchtop NMR presents an affordable alternative.
Methods
We compared the predictive performance of partial least squares discrimination analysis (PLS‐DA) models trained on low‐field 60 MHz benchtop proton (1H) NMR and high‐field 400 MHz 1H NMR spectra. The data were acquired from a sample set consisting of 49 extra virgin olive oils (EVOOs) and 45 other edible oils.
Results
We demonstrate that PLS‐DA models trained on low‐field NMR spectra are highly predictive when classifying EVOOs from other oils and perform comparably to those trained on high‐field spectra. We demonstrated that variance was primarily driven by regions of the spectra arising from olefinic protons and ester protons from unsaturated fatty acids in models derived from data at both field strengths.
This study compares the performance of partial least squares discrimination analysis (PLS‐DA) models trained on low‐field (LF) and high‐field (HF) nuclear magnetic resonance (NMR) spectra when distinguishing extra virgin olive oil (EVOO) from other edible oils. When predicting on an external dataset, LF NMR models were highly effective in classifying EVOO and had predictive performance comparable to HF models. These findings support LF NMR trained machine learning algorithms as a rapid, cost‐effective tool for EVOO authentication.
Background
The National Cancer Institute issued a Request for Information (RFI; NOT-CA-23-007) in October 2022, soliciting input on using and reusing metabolomics data. This RFI aimed to gather input ...on best practices for metabolomics data storage, management, and use/reuse.
Aim of review
The nuclear magnetic resonance (NMR) Interest Group within the Metabolomics Association of North America (MANA) prepared a set of recommendations regarding the deposition, archiving, use, and reuse of NMR-based and, to a lesser extent, mass spectrometry (MS)-based metabolomics datasets. These recommendations were built on the collective experiences of metabolomics researchers within MANA who are generating, handling, and analyzing diverse metabolomics datasets spanning experimental (sample handling and preparation, NMR/MS metabolomics data acquisition, processing, and spectral analyses) to computational (automation of spectral processing, univariate and multivariate statistical analysis, metabolite prediction and identification, multi-omics data integration, etc
.
) studies.
Key scientific concepts of review
We provide a synopsis of our collective view regarding the use and reuse of metabolomics data and articulate several recommendations regarding best practices, which are aimed at encouraging researchers to strengthen efforts toward maximizing the utility of metabolomics data, multi-omics data integration, and enhancing the overall scientific impact of metabolomics studies.
Background: Recent reports indicate that disease-specific educational modules have resulted in improved knowledge among resident physicians. These findings suggest that graduate level health ...professional students may also benefit from similar strategies focused on arthritis, the leading
cause of disability in the United States (U.S.). The purpose of this pilot study was to examine arthritis knowledge among healthcare professional students whose current curriculums include didactic arthritis content. Methods: A survey of arthritis knowledge was developed to examine general
arthritis knowledge and the epidemiological impact of arthritis among healthcare professional students. The survey was administered to 164 first, second, and third year students enrolled in graduate occupational and physical therapy programs. Results: The findings of the current study address
risk factors recognition and arthritis knowledge. Risk factors recognition - 94% identified age; 68% identified gender; 94% identified genetics; 90% identified joint injuries; 73% identified obesity as a risk factor; and 55% identified occupation. More than 50% of the students identified the
six risk factors most likely to lead to arthritis. Arthritis knowledge: prevalence, disability impact, and cost - 100% correctly identified arthritis symptoms; 26% of the students surveyed reported arthritis as the third leading cause of disability; 85% of the survey respondents reported that
in the U.S. women have higher rates of arthritis; and 31% knew the health care cost of arthritis in the U.S. Conclusions: All students recognized the symptoms of arthritis and most recognized its individual risk factors, but few exhibited knowledge of the financial and disability burden associated
with arthritis. These findings suggested that despite didactic arthritis content in both the occupational and physical therapy programs arthritis risk factors recognition and arthritis knowledge were mixed. Further research examining arthritis knowledge among a broader range of health professional
students may be important to determine if disease-specific educational modules are needed in all graduate health professional programs.
While the total number of women earning bachelor's degrees has consistently increased over time, the representation of women across STEM fields varies greatly, ranging from as high as 60% in biology ...(fraction of bachelor's degrees awarded) to as low as 20% in physics and engineering. The growth and diversification of STEM is important not only for achieving equality within these fields, but it has also been shown to encourage collaboration and to increase output, leading to a more productive branch of the economy. The STEP UP project seeks to increase the representation of women in physics. This is expected to be achieved through the implementation of research-based lesson materials into high school physics courses. Women constitute roughly half of all high school physics students, so it is crucial that we address the issue of underrepresentation at this critical point in a student's career. If the lessons achieve their desired outcome, the number of women enrolling in physics programs across the country will increase. Two lessons were developed and given to teachers: the Women in Physics lesson, which focuses on the underrepresentation of women in physics, centered around an in-class discussion on the topic; and the Careers in Physics lesson, which focuses on careers achievable with a physics bachelor's degree. We conducted this study in two phases, a pilot study in Fall 2017 followed by an experimental study in Fall 2018. The pilot study involved a select group of master physics teachers from around the country and provided preliminary data on the effectiveness of the lessons and informed revisions. The experimental study consisted of a stratified random sample of 26 physics teachers from Texas, Florida, and Maryland. Each lesson includes interactive presentations, class discussions, and student writing assignments. In this work, we examine the careers lesson specifically and analyze student work and survey results. We coded for emerging themes in the students' written assignments, and identified instances where students were able to connect the skills obtained through a physics education to their own preferred career path. In particular, we examined what goals students expected to achieve through a physics degree, and whether or not students were able to associate communal goals with physics. The careers in physics lesson is designed to inform students of the plethora of careers available to physics graduates with a bachelor's degree outside of academia. Once students learn about the wide range of careers available to those with a physics degree, they are hypothesized to be more able to align their own personal goals with those of a physics graduate. By aligning the goals of young women with those that can be achieved with a physics degree, it is expected that they will be more likely to consider majoring in physics.
